Nginx (pronounced "engine-x") has established itself in the market as one of the most powerful and flexible web servers and reverse proxy servers available. Designed to tackle the C10K problem—handling ten thousand simultaneous connections—Nginx has exceeded expectations by offering a high-performance, reliable, and scalable architecture. This is achieved through its asynchronous, event-driven request processing model, making it ideal for modern high-traffic web applications, including static content delivery, proxying, and load balancing.

Asynchronous programming in Python is a paradigm that enhances an application’s performance by running multiple I/O operations or other time-consuming tasks concurrently, without blocking the program’s main execution flow. This approach is especially beneficial for web applications that frequently interact with databases, file systems, or network resources, where delays in responses are quite common.

In modern web application development—particularly for projects dealing with large amounts of data, including media content—choosing a reliable and efficient data storage method is critical. Cloud storage is one of the most popular solutions, thanks to its flexibility, scalability, and accessibility. Let’s take a closer look at the advantages and disadvantages of cloud storage, as well as briefly compare some of the most popular providers.

Agile isn’t just a methodology—it’s a philosophy that revolutionized how we approach software development. It all began back in February 2001, when a group of 17 independent thought leaders gathered in Snowbird, Utah, to discuss their ideas on “lightweight” software development. Those discussions led to the creation of the “Agile Manifesto,” which set forth four core principles that still form the cornerstone of Agile:

Docker is a powerful tool that has revolutionized how we develop and deploy software through containerization. Let’s dive into what Docker is and why it has become an essential part of modern software development.

In the world of machine learning and artificial intelligence—particularly in training neural networks—one of the key aspects is the preparation and processing of input data. Within this context, reshaping data arrays plays a critically important role. In this article, we’ll explore why and how changing the shape of input data affects both the training process and the performance of models.

What Is an Activation Function?

Over the past decade, Natural Language Processing (NLP) has become one of the fastest-growing areas in artificial intelligence. At the heart of this progress are neural networks, which can analyze, interpret, translate, and even generate text, steadily approaching a level of human-like language understanding. This breakthrough has paved the way for creating more intuitive and efficient systems capable of interacting with users in natural, everyday language.

GRASP, which stands for General Responsibility Assignment Software Patterns, is a set of guiding principles for object-oriented design. These principles help developers distribute responsibilities among various classes and objects within a software system. Each principle focuses on addressing specific design challenges and ensuring code quality, scalability, and maintainability.

Big O notation is a fundamental concept in computer science and programming. It provides a standardized way to describe the efficiency of algorithms, allowing developers to understand how the execution time or memory usage of their programs will change as the size of the input data increases.